London, England, United Kingdom
Second-year Biomedical Sciences student at Queen Mary University of London, focused on the data side of biology: computational biology, data analysis, and applying machine learning to health and biological problems. Last summer I did a research placement at the Francis Crick Institute analysing flow cytometry data in Python and FlowJo. That's where the direction clicked — I'm more interested in what the data can show than the bench work itself. Since then I've been building. My main project is Vera, a full-stack web app that scores food products across nutrition, additives, and processing, with barcode scanning and better-alternative recommendations. I built the FastAPI backend, the frontend in Jinja2/vanilla JS, and deployed it on Render. Code's on my GitHub. Currently looking for internships and placements in data analysis, computational biology, or applied health research. Open to connecting.
Processed and analysed flow cytometry datasets using FlowJo and Python, applying compensation, transformation, and quality-control cleaning to prepare data for downstream analysis. Explored dimensionality reduction and clustering approaches to classify cell populations from single-cell data. Presented methods and findings to the research team.
Maintained accurate data records for student registrations and donations using Microsoft Excel, supporting day-to-day operations. Designed posters and supported community communications, including event promotion materials.
Led multi-day expeditions, coordinating navigation, time planning, and team logistics.